1. Field of the Invention
The present invention relates to a learning-type movement control apparatus that has functions of learning force-input time series patterns and performing force feedback based on the learning, wherein a force-input section and a control system interactively function.
Furthermore, the invention relates to a method for implementing the functions in the aforementioned learning-type movement control apparatus.
Still furthermore, the present invention relates to a distribution medium for a computer-readable program that allows an information processor to execute the aforementioned method.
2. Description of the Related Art
Conventionally, an operation control device, such as a joystick or a steering wheel, is used by a user to move a predetermined portion of a movable object. The object may be a transportation means, such as a four-wheel vehicle, a two-wheel vehicle, or an aircraft; or the object may be a cursor on the screen of an information processor. To move the object as the user desires, the user must operate the operation control device to issue operation commands to the object. To issue the operation commands, the user must exert predetermined forces on the operation control device in directions along which the user wishes to move the object. Namely, the user must determine options, such as the direction and the distance of the movement of the object.
In the conventional device as described above, when the above is considered on the side of the object to be moved, the operation command must be issued each time the user attempts to operate the operation control device, such as the steering wheel or the joystick. For the user to operate the object to meet his or her desire, and even when substantially the same movement is performed, the user must intermittently or continually operate the operation control device. That is, since the conventional device has no learning function in the operation control device, even to repeat a movement, the user must perform complicated and time-consuming operations with the operation control device. This is disadvantageous.
The present invention is made under the above-described circumstances. Accordingly, objects thereof are to provide:
a learning-type movement control apparatus that has the functions of learning the movement of an operation control device, predicting the movement thereof, and driving it to automatically move;
a method implementing the functions of the aforementioned learning-type movement control apparatus; and
a medium for distributing a computer-readable program that allows an information processor to execute the aforementioned method.
To achieve the aforementioned objects, according to one aspect of the present invention, a learning-type movement control apparatus comprises an operation control device, a learning section, and a predicting section. The operation control device has a predetermined portion that is displaced according to a force exerted in an arbitrary direction. The operation control device outputs the amount of the displacement at least as one-dimensional position-representing information, receives a feedback signal carrying information generated by adding displacement information to the position-representing information, and drives the predetermined portion according to a direction and a displacement that are based on the feedback signal. The learning section receives the position-representing information, which is input in time series from the operation control device, and performs learning of the movement of the operation control device. The predicting section performs prediction of a displacement of the operation control device according to the position-representing information that is input in time series from the operation control device and a result of the learning by the learning section, and generates the feedback signal by adding the displacement information to the position-representing information, and outputs the feedback signal to the operation control device.
The learning section and the predicting section may be included in a recurrent neural network that comprises an input layer, a hidden layer, and an output layer. The recurrent neural network may be of a type that performs feedback from the output layer to the input layer. In addition, the learning section may be arranged to perform the learning of the movement of the predetermined portion of the operation control device according to an error propagation method.
According to another aspect of the invention, a learning-type movement control method comprises three processing steps. A first step performs learning of a pattern of a time-series force input to an operation control device by using a recurrent neural network. A second step performs prediction of information regarding movement of a predetermined portion of the operation control device by using the recurrent neural network according to a result of the learning. A third step drives the operation control device to move according to the information regarding the movement, which has been obtained as a result of the prediction.
According to still another aspect of the present invention, a distribution medium for distributing a computer-readable program that allows an information-processing unit to execute processing which comprises three steps is provided. A first step performs learning of a pattern of a time-series force input to an operation control device by using a recurrent neural network. A second step performs prediction of information regarding movement of a predetermined portion of the operation control device by using the recurrent neural network according to a result of the learning. A third step drives the operation control device to move according to the information regarding the movement, which has been obtained as a result of the prediction.
Thus, according to the present invention, for example, a user exerts a desired force on the operation control device in a desired direction. The operation control device is thereby operated so as to perform the movement desired by the user. According to the exerted force and the direction thereof, the predetermined portion of the operation control device is displaced. The amount of the displacement is separated into two-dimensional position-representing information items (x, y). Then, the position-representing information items (x, y) are output in time series to the learning section and the predicting section.
The learning section receives the position-representing information items (x, y), and performs, for example, learning of movements of the operation control device a predetermined number of times. It learns the movements according to, for example, an error propagation method.
According to the position-representing information items (x, y) and a result of the learning by the learning section, the predicting section performs prediction of a position the operation control device at a subsequent time. Then, the predicting section adds displacement information items to the position-representing information items (x, y), thereby generates a feedback signal, and outputs it to the operation control device.
Having received the feedback signal from the predicting section, and according to directions and displacements specified by the feedback signal, the predetermined portion of the operation control device is driven in either the positive direction or the negative direction of each of the x and y directions.
The above-described operations are iterated, and during the iteration, the movement of the operation control device is incrementally learned by the learning section and is predicted by the predicting section. This allows the predetermined portion of the operation control device to operate according to the prediction without a force being exerted by the user.
In the above state, that is, when the predetermined portion of the operation control device operates according to only the instruction given by the feedback signal, the user can exert a desired force in a desired direction on the operation control device. Accordingly, the position-representing information items (x, y) regarding the movement at the particular time are output in time series.
Then, according to the interaction of the learning section, the predicting section, and the driving section, the new movement is learned. The result of the learning allows prediction information to be provided. According to the prediction information, without a force being exerted by the user, the predetermined portion of the operation control device becomes enabled to implement the new movement.
Thus, the present invention is advantageous in that it provides a practically effective system in which, without complicated operations being performed, the movement of the operation control device is learned, and the movement is thereby predicted to allow the operation control device to automatically move.